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training.py
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training.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Sep 20 20:19:50 2018
@author: USER
"""
import cv2
import fiturTekstur as ft
import fiturWarna as fw
import csv
import segmentasiWarna as sg
import numpy as np
import time
import os
def resizeImg(image):
#img = cv2.imread(filename)
small = cv2.resize(image, (0,0),fx=0.1,fy=0.1)
return small
start_time = time.time()
np.seterr(all='warn')
Y = 1
with open('data/dataTekstur.csv', 'a') as myfile:
wr = csv.writer(myfile, delimiter=',')
for filename in os.listdir("D:\\KULIAH\SEMESTER VII\\SKRIPSI - OFFLINE\\Ahmad Fauzi A _ Akhmad Muzanni S\\Segmentasi_All\\"):
if (Y <2000):
#filename = '001_0001_XiaomiRedmiNote4X.jpg'
#strFile = 'D:\\KULIAH\\SEMESTER VII\\SKRIPSI - OFFLINE\\Ahmad Fauzi A _ Akhmad Muzanni S\\All\\001_0001_XiaomiRedmiNote4X.jpg'
strFile = 'D:\\KULIAH\\SEMESTER VII\\SKRIPSI - OFFLINE\\Ahmad Fauzi A _ Akhmad Muzanni S\\Segmentasi_All\\'+filename
rgbImg = cv2.imread(strFile)
#rgbImg = resizeImg(rgbImg)
#cv2.imshow('ASLI',rgbImg)
print(filename[:8])
# TEXTURE FEATURE EXTRACTION
coMatrix0, coMatrix45, coMatrix90, coMatrix135 = ft.getCoMatrix(rgbImg)
sumCoMatrix0 = ft.sumCM(coMatrix0)
sumCoMatrix45 = ft.sumCM(coMatrix45)
sumCoMatrix90 = ft.sumCM(coMatrix90)
sumCoMatrix135 = ft.sumCM(coMatrix135)
meanX0, meanY0, varX0, varY0, energy0, entropy0, contrast0, dissimilarity0, homogeneity0, correlation0 = ft.getFeature(coMatrix0, sumCoMatrix0)
meanX45, meanY45, varX45, varY45, energy45, entropy45, contrast45, dissimilarity45, homogeneity45, correlation45 = ft.getFeature(coMatrix45, sumCoMatrix45)
meanX90, meanY90, varX90, varY90, energy90, entropy90, contrast90, dissimilarity90, homogeneity90, correlation90 = ft.getFeature(coMatrix90, sumCoMatrix90)
meanX135, meanY135, varX135, varY135, energy135, entropy135, contrast135, dissimilarity135, homogeneity135, correlation135 = ft.getFeature(coMatrix135, sumCoMatrix135)
fiturTekstur = []
fiturTekstur.append(meanX0)
fiturTekstur.append(meanY0)
fiturTekstur.append(varX0)
fiturTekstur.append(varY0)
fiturTekstur.append(energy0)
fiturTekstur.append(entropy0)
fiturTekstur.append(contrast0)
fiturTekstur.append(dissimilarity0)
fiturTekstur.append(homogeneity0)
fiturTekstur.append(correlation0)
fiturTekstur.append(meanX45)
fiturTekstur.append(meanY45)
fiturTekstur.append(varX45)
fiturTekstur.append(varY45)
fiturTekstur.append(energy45)
fiturTekstur.append(entropy45)
fiturTekstur.append(contrast45)
fiturTekstur.append(dissimilarity45)
fiturTekstur.append(homogeneity45)
fiturTekstur.append(correlation45)
fiturTekstur.append(meanX90)
fiturTekstur.append(meanY90)
fiturTekstur.append(varX90)
fiturTekstur.append(varY90)
fiturTekstur.append(energy90)
fiturTekstur.append(entropy90)
fiturTekstur.append(contrast90)
fiturTekstur.append(dissimilarity90)
fiturTekstur.append(homogeneity90)
fiturTekstur.append(correlation90)
fiturTekstur.append(meanX135)
fiturTekstur.append(meanY135)
fiturTekstur.append(varX135)
fiturTekstur.append(varY135)
fiturTekstur.append(energy135)
fiturTekstur.append(entropy135)
fiturTekstur.append(contrast135)
fiturTekstur.append(dissimilarity135)
fiturTekstur.append(homogeneity135)
fiturTekstur.append(correlation135)
#print(fiturTekstur)
# COLOR FEATURE EXTRACTION
#Lab = fw.convBGRtoLAB(rgbImg)
'''
segmentImg = sg.segmentation(rgbImg)
#meanL, varL, skewL = fw.getColorMoment(segmentImg[:,:,0])
#meanA, varA, skewA = fw.getColorMoment(segmentImg[:,:,1])
#meanB, varB, skewB = fw.getColorMoment(segmentImg[:,:,2])
meanL, varL, skewL, kurtL = fw.getColorMoment(segmentImg[:,:,0])
meanA, varA, skewA, kurtA = fw.getColorMoment(segmentImg[:,:,1])
meanB, varB, skewB, kurtB = fw.getColorMoment(segmentImg[:,:,2])
fiturWarna = []
fiturWarna.append(meanL)
fiturWarna.append(varL)
fiturWarna.append(skewL)
fiturWarna.append(kurtL)
fiturWarna.append(meanA)
fiturWarna.append(varA)
fiturWarna.append(skewA)
fiturWarna.append(kurtA)
fiturWarna.append(meanB)
fiturWarna.append(varB)
fiturWarna.append(skewB)
fiturWarna.append(kurtB)
#print(fiturWarna)
#cv2.imshow('SEGMENTASI',segmentImg)
'''
fitur = []
fitur.append(filename[:8])
for i in fiturTekstur:
fitur.append(i)
#for i in fiturWarna:
#fitur.append(i)
#cv2.imwrite('D:\\KULIAH\\SEMESTER VII\\SKRIPSI - OFFLINE\\Ahmad Fauzi A _ Akhmad Muzanni S\\Segmentasi_All\\'+filename[:8]+'.jpg',segmentImg)
#fitur = fitur.extend(fiturTekstur)
#fitur = fitur.extend(fiturWarna)
wr.writerow(fitur)
print(time.time() - start_time)
Y+=1
print(time.time() - start_time)
cv2.waitKey(0)